The School of Dental Medicine, University of Zagreb is the key and most recognizable institution of dental medicine in Croatia. For the F2 SEO cluster, this article represents core dentistry: Zagreb is the main article for the dental faculty, while Split and Rijeka can strategically be covered through long-tail terms such as dental medicine, faculty of dental medicine, dental medicine study program and clinical research in dental medicine. Because dental research combines clinical dentistry, oral health, periodontology, orthodontics, prosthodontics, oral surgery, dental materials and doctoral research, statistical data analysis plays a central role.
Students, doctoral candidates and researchers often work with clinical dental data, oral health indices, periodontal measurements, orthodontic parameters, radiological findings, quality-of-life questionnaires, epidemiological data, laboratory measurements of dental materials, longitudinal patient follow-up and treatment outcomes. This article belongs to the F2 hub: statistical help for clinical and scientific research at medical faculties in Croatia.
Statistical data analysis for the School of Dental Medicine, University of Zagreb
The School of Dental Medicine, University of Zagreb is the key and most recognizable institution of dental medicine in Croatia. In the SEO strategy for the F2 cluster, this article should have the status of the core dentistry article because it covers main searches related to Stomatološki fakultet Zagreb, Stomatološki fakultet Sveučilišta u Zagrebu, SFZG, dental medicine Zagreb, dentistry Zagreb and statistical data analysis in dental medicine.
It is important to distinguish Zagreb from other cities. Zagreb is the core dental article because the School of Dental Medicine, University of Zagreb is the traditional and most recognizable institution of dental medicine. Split and Rijeka have strong potential through long-tail terms: dental medicine Split, dental medicine Rijeka, faculty of dental medicine, study of dental medicine, doctors of dental medicine and clinical research in dental medicine. This structure helps avoid keyword cannibalization and builds a clear topical hierarchy.
Dental research differs from general medical research because it often includes specific clinical indices, oral cavity measurements, dental materials, periodontal parameters, orthodontic analyses, prosthodontic outcomes, oral surgery procedures, radiological measures, aesthetic assessments, oral health-related quality of life and longitudinal follow-up of treatment outcomes.
At StatistischeBeratung.de, professional support is provided throughout the research process — from study design and sample size planning to dataset structuring, method selection, SPSS analysis, interpretation and table preparation. The author remains responsible for the final text and interpretation. This article belongs to the F2 hub: statistical help for clinical and scientific research at medical faculties in Croatia.
Specific characteristics of research at the School of Dental Medicine Zagreb
Research at the School of Dental Medicine Zagreb may include preventive dental medicine, restorative dental medicine, periodontology, orthodontics, prosthodontics, oral surgery, oral medicine, pediatric dentistry, radiology, implantology, dental materials, oral health epidemiology and public health dental topics.
A key feature of dental research is that outcomes are often measured at the level of the patient, tooth, tooth surface, implant, restoration or treatment procedure. This means that data may be hierarchical: several teeth belong to one patient, several measurements may be taken on the same tooth and several follow-up visits may belong to the same treatment.
Data types in dental papers
Projects may include demographic data, clinical dental outcomes, oral health indices, DMFT indicators, periodontal indices, probing depth, bleeding on probing, attachment loss, orthodontic measurements, cephalometric parameters, radiological findings, prosthodontic outcomes, implant parameters, treatment success, pain, patient satisfaction, oral health-related quality of life and laboratory testing of dental materials.
Questionnaire studies may include instrument validation, scale reliability, factor structure, correlations between subjective and clinical indicators, and group differences. In dentistry, questionnaires on oral health-related quality of life, dental anxiety, treatment satisfaction and aesthetic perception are especially important.
Research design in dental medicine
Cross-sectional oral health studies
Cross-sectional studies are often used to assess prevalence of caries, periodontal disease, orthodontic anomalies, oral hygiene habits, quality of life or patient attitudes at a single time point.
Retrospective clinical analyses
Retrospective studies use clinical records, radiological findings, orthodontic documentation, prosthodontic records or treatment logs. Challenges include missing values, inconsistent documentation and limited control over original measurements.
Prospective clinical studies
Prospective studies allow better planning of measurements, follow-up visits, treatment outcomes and success criteria. Primary and secondary outcomes, sample size and analysis plan should be defined in advance.
Longitudinal studies and repeated measurements
Longitudinal studies follow patients over time, for example before and after therapy, during orthodontic treatment, after implantation or through follow-up visits. Such data require methods that account for dependent measurements.
Laboratory research on dental materials
Laboratory studies may include strength, hardness, adhesion, roughness, color change, wear, material resistance or comparison of dental materials and processing procedures. ANOVA, post-hoc tests, regression and correlations are often used.
Important statistical methods
Descriptive statistics describe sample structure: age, sex, dental status, clinical characteristics, oral health indices and treatment outcomes. Depending on distribution, mean and standard deviation or median and interquartile range are reported.
Group comparisons use t-test, Mann-Whitney U test, ANOVA, Kruskal-Wallis test, chi-square test and Fisher’s exact test. Examples include comparisons by age, sex, treatment, material, orthodontic group or oral health status.
ANOVA is especially useful in laboratory and clinical dental studies when several materials, treatments, patient groups or measurement conditions are compared. Post-hoc tests are used after significant results.
Correlation analysis examines relationships between dental indices, quality of life, pain, age, hygiene habits, periodontal indicators, orthodontic measurements or material properties.
Linear, logistic and ordinal regression are used to evaluate predictors of dental outcomes. Logistic regression is useful for binary outcomes such as caries presence, treatment success, complication, implant loss or positive radiological finding.
ROC analysis can evaluate diagnostic accuracy of a clinical indicator, radiological measure, biomarker or test for identifying a dental condition.
Reliability analysis and instrument validation include Cronbach’s alpha, item analysis, factor analysis, correlations and construct validity.
SPSS analysis and interpretation
SPSS is frequently used in dental papers because it supports group comparisons, correlations, regression, ROC analysis, reliability analysis and graphical presentation. Technical execution alone is not enough; interpretation must be dental and clinical.
A p-value shows statistical significance, but not automatically effect size, clinical importance or applicability. Confidence intervals, effect sizes, odds ratios, AUC values and other indicators are therefore important.
Sample size and statistical power
Dental studies often require sample size planning at the level of patients, teeth, implants, restorations, material samples or measurement units. It is especially important not to confuse the number of teeth with the number of independent patients.
Typical topics for Zagreb
Typical topics include dental medicine, caries, periodontology, orthodontics, prosthodontics, oral surgery, implantology, pediatric dentistry, preventive dentistry, radiology, oral health, quality of life, dental materials, dental anxiety, aesthetic outcomes, epidemiology of oral health, questionnaire validation and comparison of treatment procedures.
SEO structure: Zagreb core, Split and Rijeka long-tail
For the F2 SEO strategy, Zagreb should be the main core article for dentistry and the School of Dental Medicine. Split and Rijeka can be covered through long-tail terms such as dental medicine, faculty of dental medicine, dental medicine study program, dental hygiene, dental technology, clinical dental research and local SEO variations.
Workflow
The workflow includes reviewing the topic and hypotheses, checking dataset structure, defining primary and secondary outcomes, selecting statistical methods, SPSS analysis, table preparation and interpretation. I prepare statistical results and suggest how to present them in the academic paper. The author remains responsible for the final text and interpretation.
FAQ
Can clinical dental data be analyzed?
Yes. Dental indices, periodontal parameters, orthodontic measurements, implant outcomes, radiological findings and treatment results can be analyzed.
Can tooth-level or implant-level data be analyzed?
Yes, but the data structure must be considered because several teeth or implants may belong to the same patient.
Can dental materials be analyzed?
Yes. Laboratory studies of dental materials often use ANOVA, post-hoc tests, correlations and regression.
Is SPSS sufficient for a dental paper?
For many student papers, dissertations and scientific papers, SPSS is sufficient. More complex hierarchical data may require additional models.
Keywords
statistics School of Dental Medicine Zagreb, Stomatološki fakultet Zagreb statistics, SFZG SPSS, dental medicine Zagreb statistics, dentistry Zagreb statistics, statistical data analysis dentistry, periodontology statistics, orthodontics statistics, dental materials statistics, implantology statistics
Metatext
Statistical data analysis for the School of Dental Medicine, University of Zagreb: SPSS, dental medicine, dentistry, periodontology, orthodontics, implantology, dental materials and clinical research.
